# bokeh python Reviews **Vendor:** bokeh python **Category:** [Component Libraries Software](https://www.g2.com/categories/component-libraries) **Average Rating:** 4.2/5.0 **Total Reviews:** 10 ## About bokeh python Bokeh is an interactive visualization library for Python that enables beautiful and meaningful visual presentation of data in modern web browsers. With Bokeh, you can quickly and easily create interactive plots, dashboards, and data applications. ## bokeh python Reviews ### 1. Love using bokeh for interactive plots **Rating:** 5.0/5.0 stars **Reviewed by:** Clare S. | Research and Instrumentation Analyst, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** March 05, 2019 **What do you like best about bokeh python?** I like how there are a several pre made interactive plot templates that allow you to generate interactive plots in one line of code, but that there is also room for customization beyond that. It's pretty easy to get started with bokeh to make simple yet useful interactive plots and web pages. **What do you dislike about bokeh python?** I've had some issues getting certain features to work that I've ended up just giving up on. There's a learning curve when trying to make very custom things, without a lot of documentation. It's also difficult to debug and requires learning some javascript, which is useful but increases the learning curve. **Recommendations to others considering bokeh python:** I'd recommend this package to users. **What problems is bokeh python solving and how is that benefiting you?** I use Bokeh to make interactive plots for my team at work to use. We use these to monitor the health of the scientific instrument we work on and it's useful to have these over static plots. The screen shot I attached it part of an interactive web page I made with bokeh that allows you to filter data from out instrument from a specific subset to display, and then to download a table. ### 2. Data visualization in Python for advaned analytics **Rating:** 4.0/5.0 stars **Reviewed by:** Dorian N. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 28, 2019 **What do you like best about bokeh python?** I like the bokeh Python package because it lets me visualize data in ways previously unachievable. This package allows me to drive analytics in a way that impresses my team. It's really changed the way we do data engineering on our team. **What do you dislike about bokeh python?** I dislike this package because it is somewhat hard to use at times best the documentation is not the best and sometimes unclear. This package definitely needs better documentation written and shared. **What problems is bokeh python solving and how is that benefiting you?** The problems I'm solving with this package is improving and updating our methods of running analysis of various financial datasets. I am the pioneer on the team looking for solutions that can replace our enterprise level solutions that we have in place with open source tools that are just as good. ### 3. Data visualization made easy in python! **Rating:** 4.5/5.0 stars **Reviewed by:** Alex J. | Data Analyst, Mid-Market (51-1000 emp.) **Reviewed Date:** July 23, 2019 **What do you like best about bokeh python?** I love bokeh library in python because it allows me to programmatically create data visualizations for analytics work in ways not previously possible where we used slow clunky software. **What do you dislike about bokeh python?** I dislike that bokeh python is completely open source and has no paid support. It would be great if open source products had better support. **What problems is bokeh python solving and how is that benefiting you?** The problems I am solving with bokeh python is a team oriented analytics workflow that scales. Bokeh python does exactly that and I am very happy to say that the benefits out-weighted the initial confusion when we got started with this package. ### 4. A picture is worth a thousand words, a good graph is worth even more **Rating:** 5.0/5.0 stars **Reviewed by:** Paolo D. | Software Developer in Test, Mid-Market (51-1000 emp.) **Reviewed Date:** January 17, 2019 **What do you like best about bokeh python?** With bokeh, I can create interactive graphs which gave a whole new dimension to my performance testing reports. Not only they look beautiful, but they let me illustrate concepts in an interactive way, without generating different graphs which are only zoomed in versions or simple numbers: I can show the numbers by hovering over the generated graph instead **What do you dislike about bokeh python?** it took me a while to get the right configuration. Matplotlib works almost out of the box, bokeh takes very little to produce a nice graph, but quite some work to get exactly what you want. Anyway, this is justified by the fact the final outcome is more captivating than Matplotlib and interactive **Recommendations to others considering bokeh python:** Watch out for the NumPy dependency: it might be tricky to install on some OS. Apart from this, installation was smooth and the learning curve shallow enough to start producing logs within the first few minutes of usage **What problems is bokeh python solving and how is that benefiting you?** I managed to automate the full performance testing process by replacing the old tool we were using. I don't need to rely anymore on a black box third party, which produced only certain graphs, I can customize the output I want and format them in a more intelligible way In addition, inspection for individual results (over millions of samples) is much easier ### 5. Data analytics made easy in python **Rating:** 4.5/5.0 stars **Reviewed by:** John Paul S. | Rewards Live, Mid-Market (51-1000 emp.) **Reviewed Date:** July 20, 2019 **What do you like best about bokeh python?** I like bokeh python because it allows me to streamline my data analytics workflows so I can better showcase different types of data to a large audience. It makes data easier to understand with the various types of graphs. **What do you dislike about bokeh python?** I dislike that bokeh is an open source library that is somewhat hard to understand in its documentation form, perhaps because very advanced individuals wrote it. **What problems is bokeh python solving and how is that benefiting you?** The problems I'm solving with bokeh python is the need to illustratively show what's going on from an analytics perspective. It has drastically sped up the pace at which we work. ### 6. Data visualization library **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** March 04, 2019 **What do you like best about bokeh python?** Bokeh allows me and my team to visualize data and information in a way that previously wasnt possible with the cluncky BI tools that we used to use. I think what I love best about bokeh is how easy it is to install and use because it's open source. **What do you dislike about bokeh python?** With open source comes the issue with support. There isn't much support available besides a developer guide which is available on their website so you better have a team of engineers ready to dive deep. **Recommendations to others considering bokeh python:** This is a great library to test and use. The documentation is clear and understandable if you have a development team. All in all, good library to try out **What problems is bokeh python solving and how is that benefiting you?** The business problems solved with bokeh are varied. The benefits that I have realized is the ability to visualize data using advanced statistical methods that tools like Tableau and IBM Cognos simply cannot. ### 7. Data science at it's finest **Rating:** 5.0/5.0 stars **Reviewed by:** Dan G. | Analyst, Technology, Small-Business (50 or fewer emp.) **Reviewed Date:** March 05, 2019 **What do you like best about bokeh python?** Bokeh is a phenomenal visualization library in Python. As a data scientist, you're constantly looking for ways to express data in more understandable manner and Bokeh lets you do just that. **What do you dislike about bokeh python?** I think what I dislike about this library is the learning curve. It's not easy to learn each new function and takes time. **Recommendations to others considering bokeh python:** Bokeh is a library that every business should learn to use and strive to understand so they can improve their data science skills. **What problems is bokeh python solving and how is that benefiting you?** Bokeh lets me and our team of data scientists better visualize data and know exactly what's going on with ever-growing datasets. ### 8. Bokeh: Great interactive, simple visualizations. Nearly as good as plotly **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in E-Learning | Mid-Market (51-1000 emp.) **Reviewed Date:** January 30, 2019 **What do you like best about bokeh python?** I like that it's fairly easy to create dynamic html visualizations that look slick and feel good. Since I learned R before python for statistics and visualizations, I definitely prefer R's ggplot2 syntax (which plotly can then easily convert to an html version with plotly::ggplotly()). However, for the python work that I do (when my coworkers prefer python notebooks, etc.) the capability of bokeh is great! The api is fairly consistent across different types of plots which is great. **What do you dislike about bokeh python?** While bokeh is pretty strong for creating pretty slice visualizations, I find it more difficult to customize plot themes and features as compared to some other visualization libraries. However, I also find myself more impressed with the default settings of any bokeh plot. **Recommendations to others considering bokeh python:** Static visualizations, probably start with seaborn (don't use matplotlib unless you know what you're doing). Dynamic visualizations, definitely learn bokeh, maybe also plotly **What problems is bokeh python solving and how is that benefiting you?** We typically use bokeh as an open source way of quickly visualizing a new dataset in several ways that we can than share an internal URL or flat html page with other coworkers or management. The ability to send off an html file to some other person and allow them to explore the data easily makes my job a lot more self-serve and easier. I find it great for allowing management to find their own insights from raw data. ### 9. Bokeh library for visualization **Rating:** 3.5/5.0 stars **Reviewed by:** Bisma B. | Data Analyst, Information Technology and Services, Mid-Market (51-1000 emp.) **Reviewed Date:** January 29, 2019 **What do you like best about bokeh python?** The library has a lot of potential to create a rainbow of visualizations. I like that the dashboards are interactive. **What do you dislike about bokeh python?** The help resources or learning resources are limited. **What problems is bokeh python solving and how is that benefiting you?** Creating BI dashboards. Benefits are customization because bokeh is used with python which makes it highly customizable ### 10. Good viz library **Rating:** 2.5/5.0 stars **Reviewed by:** Verified User in Oil & Energy | Small-Business (50 or fewer emp.) **Reviewed Date:** March 03, 2019 **What do you like best about bokeh python?** Easy to learn and use, good for basic interactive charts. Allows you to provide charts in many mediums (html, notebook and server). Good alternative to plotly and pygal. **What do you dislike about bokeh python?** Plotly offers a much greater level of interactivity than bokeh out of the box. bokeh has a problem with its documentation. **What problems is bokeh python solving and how is that benefiting you?** Data vizualization - [View bokeh python pricing details and edition comparison](https://www.g2.com/products/bokeh-python/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-01+06%3A57%3A16+-0500&secure%5Bsession_id%5D=06779f6e-fd8e-4a24-beaf-1e927e5fff53&secure%5Btoken%5D=66c442f54c7f7466f19901a23419286c58c2db5ced29c4b3f63cd5d4e1f409ba&format=llm_user) ## bokeh python Features **Functionality** - Language Contingency - Component Library - Unlocked Components **Management** - Framework Integration - Repository Management - Support ## Top bokeh python Alternatives - [DevExpress](https://www.g2.com/products/devexpress/reviews) - 4.8/5.0 (112 reviews) - [Essential Studio](https://www.g2.com/products/essential-studio/reviews) - 4.5/5.0 (705 reviews) - [Progress Kendo UI](https://www.g2.com/products/progress-kendo-ui/reviews) - 4.4/5.0 (248 reviews)